Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
will primarily support the Head of School (Professor George Panoutsos, Chair in Computational Intelligence) and his research activities in the area of Machine Learning (ML) for Engineering, focusing
-
along the Booster Neutrino Beamline at Fermilab, USA. Each detector in the SBN programme utilises the liquid argon time projection chamber (LArTPC) technology. The main goal of the SBN programme is to
-
Computational analysis of the flow through aerofoil cascades School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof Mohamed Pourkashanian, Prof Lin Ma, Prof
-
Neuro-Symbolic Methods for Explanation-Based Reasoning with Large Language Models School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Marco Valentino, Prof Nikos
-
The Japanese Long-Baseline Neutrino Programme (T2K, Super-Kamiokande and Hyper-Kamiokande) School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr S Cartwright, Dr Patrick
-
EngD in Enhancing Fusion Engineering with Augmented and Virtual Reality and Digital Twins
-
A Machine Learning Enabled Physical Layer for 6G Radio Systems School of Electrical and Electronic Engineering PhD Research Project Directly Funded UK Students Prof Timothy O'Farrel, Prof Mohammed
-
Development and validation of control strategies for flexible and demand-driven anaerobic digestion School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof
-
Developing a Developmentally Appropriate AI Chatbot to Support Young People with Inflammatory Bowel Disease Transitioning to Adult Healthcare School of Computer Science PhD Research Project Directly
-
Unsteady Turbulent Flow in Turbomachinery School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof S He Application Deadline: Applications accepted all year round